{"id":17728,"date":"2022-07-04T05:26:14","date_gmt":"2022-07-04T05:26:14","guid":{"rendered":"https:\/\/club.informatix.co.jp\/?p=17728"},"modified":"2024-10-31T07:20:37","modified_gmt":"2024-10-31T07:20:37","slug":"numpy%e3%81%a7%e8%a1%8c%e5%88%97%e3%80%80%e5%9b%9e%e5%b8%b0%e5%88%86%e6%9e%90-%e3%81%9d%e3%81%ae1%ef%bd%9cpython%e3%81%a7%e6%95%b0%e5%ad%a6%e3%82%92%e5%ad%a6%e3%81%bc%e3%81%86%ef%bc%81%e3%80%80","status":"publish","type":"post","link":"https:\/\/club.informatix.co.jp\/?p=17728","title":{"rendered":"NumPy\u3067\u884c\u5217\u3000\u56de\u5e30\u5206\u6790 \u305d\u306e1\uff5cPython\u3067\u6570\u5b66\u3092\u5b66\u307c\u3046\uff01 \u7b2c22\u56de"},"content":{"rendered":"\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_83 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">\u76ee\u6b21<\/p>\n<label for=\"ez-toc-cssicon-toggle-item-6a1331dfaec91\" class=\"ez-toc-cssicon-toggle-label\"><span class=\"\"><span 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>\uff08\u8eab\u9577\u3068\u4f53\u91cd\uff09\u56de\u5e30\u5206\u6790\u30d7\u30ed\u30b0\u30e9\u30e0\u3000\u300cregression1.py\u300d<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/club.informatix.co.jp\/?p=17728\/#%E5%AE%9F%E8%A1%8C%E7%B5%90%E6%9E%9C\" >\u5b9f\u884c\u7d50\u679c<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/club.informatix.co.jp\/?p=17728\/#%EF%BC%88%E8%BA%AB%E9%95%B7%E3%81%A8%E4%BD%93%E9%87%8D%EF%BC%89%E5%9B%9E%E5%B8%B0%E5%88%86%E6%9E%90%E3%83%97%E3%83%AD%E3%82%B0%E3%83%A9%E3%83%A0%E3%80%8Cregression2py%E3%80%8D\" >\uff08\u8eab\u9577\u3068\u4f53\u91cd\uff09\u56de\u5e30\u5206\u6790\u30d7\u30ed\u30b0\u30e9\u30e0\u300cregression2.py\u300d<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/club.informatix.co.jp\/?p=17728\/#%E5%AE%9F%E8%A1%8C%E7%B5%90%E6%9E%9C-2\" >\u5b9f\u884c\u7d50\u679c<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/club.informatix.co.jp\/?p=17728\/#numpypolyfit%E9%96%A2%E6%95%B0%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%9F%E5%9B%9E%E5%B8%B0%E5%88%86%E6%9E%90\" >numpy.polyfit\u95a2\u6570\u3092\u4f7f\u3063\u305f\u56de\u5e30\u5206\u6790<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/club.informatix.co.jp\/?p=17728\/#%EF%BC%88%E8%BA%AB%E9%95%B7%E3%81%A8%E4%BD%93%E9%87%8D%EF%BC%89%E5%9B%9E%E5%B8%B0%E5%88%86%E6%9E%90%E3%83%97%E3%83%AD%E3%82%B0%E3%83%A9%E3%83%A0%E3%80%8Cregression3py%E3%80%8D\" >\uff08\u8eab\u9577\u3068\u4f53\u91cd\uff09\u56de\u5e30\u5206\u6790\u30d7\u30ed\u30b0\u30e9\u30e0\u300cregression3.py\u300d<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/club.informatix.co.jp\/?p=17728\/#%E5%AE%9F%E8%A1%8C%E7%B5%90%E6%9E%9C-3\" >\u5b9f\u884c\u7d50\u679c<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/club.informatix.co.jp\/?p=17728\/#%E5%9B%9E%E5%B8%B0%E5%88%86%E6%9E%90%E3%81%AE%E9%8D%B5%E3%80%8C%E6%9C%80%E5%B0%8F2%E4%B9%97%E6%B3%95%E3%80%8D\" >\u56de\u5e30\u5206\u6790\u306e\u9375\u300c\u6700\u5c0f2\u4e57\u6cd5\u300d<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"%E7%B7%9A%E5%BD%A2%E4%BB%A3%E6%95%B0%E3%81%AF%E3%82%BF%E3%82%A4%E3%83%98%E3%83%B3\"><\/span>\u7dda\u5f62\u4ee3\u6570\u306f\u30bf\u30a4\u30d8\u30f3<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><a href=\"https:\/\/club.informatix.co.jp\/?p=17472\" target=\"_blank\" rel=\"noopener\">\u524d\u56de<\/a>\u30fb<a href=\"https:\/\/club.informatix.co.jp\/?p=17109\" target=\"_blank\" rel=\"noopener\">\u524d\u3005\u56de<\/a>\u3001\u30d9\u30af\u30c8\u30eb\u3092\u53d6\u308a\u4e0a\u3052\u307e\u3057\u305f\u3002\u30d9\u30af\u30c8\u30eb\u306e\u6b21\u3068\u3044\u3046\u3053\u3068\u3067\u884c\u5217\u3092\u306f\u3058\u3081\u3066\u3044\u304d\u307e\u3059\u3002\u30d9\u30af\u30c8\u30eb\u3068\u884c\u5217\u306f\u7dda\u5f62\u4ee3\u6570\u5b66\u3068\u3044\u3046\u5927\u304d\u306a\u6570\u5b66\u3078\u3068\u7d50\u5b9f\u3057\u307e\u3059\u3002<\/p>\n<p>1\u518a\u306b\u307e\u3068\u3081\u3089\u308c\u305f\u7dda\u5f62\u4ee3\u6570\u306e\u30c6\u30ad\u30b9\u30c8\u3092\u81ea\u529b\u3067\u7d42\u308f\u3089\u305b\u308b\u306b\u306f\u3001\u76f8\u5f53\u306a\u6839\u6027\u3068\u5b9f\u529b\u304c\u5fc5\u8981\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n<p><img decoding=\"async\" class=\"aligncenter wp-image-17742 size-full\" src=\"https:\/\/club.informatix.co.jp\/wp-content\/uploads\/2022\/07\/20220701-1.jpg\" alt=\"\" width=\"800\" height=\"479\" srcset=\"https:\/\/club.informatix.co.jp\/wp-content\/uploads\/2022\/07\/20220701-1.jpg 800w, https:\/\/club.informatix.co.jp\/wp-content\/uploads\/2022\/07\/20220701-1-300x180.jpg 300w, https:\/\/club.informatix.co.jp\/wp-content\/uploads\/2022\/07\/20220701-1-768x460.jpg 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/><\/p>\n<p><a href=\"https:\/\/club.informatix.co.jp\/?p=17472\" target=\"_blank\" rel=\"noopener\">\u524d\u56de<\/a>\u53d6\u308a\u4e0a\u3052\u305f\u30b3\u30b5\u30a4\u30f3\u985e\u4f3c\u5ea6\u3068\u306f\u3001\u30c7\u30fc\u30bf\u3092\u30d9\u30af\u30c8\u30eb\u5316\u3059\u308b\u3053\u3068\u3067n\u6b21\u5143\u7a7a\u9593\u306b\u304a\u3051\u308b2\u3064\u306en\u6b21\u5143\u30d9\u30af\u30c8\u30eb\u306e\u306a\u3059\u89d2\uff08\u5b9f\u969b\u306b\u306f\u305d\u306e\u30b3\u30b5\u30a4\u30f3\uff09\u3092\u8a08\u7b97\u3059\u308b\u3053\u3068\u3067\u6bd4\u8f03\u3059\u308b\u3068\u3044\u3046\u30a2\u30a4\u30c7\u30a3\u30a2\u3067\u3059\u3002<\/p>\n<p>\u30d9\u30af\u30c8\u30eb\u306f3\u6b21\u5143\u304c4\u6b21\u5143\u306b\u6b21\u5143\u304c\u5927\u304d\u304f\u306a\u3063\u3066\u3082\u3055\u307b\u3069\u8a08\u7b97\u304c\u9762\u5012\u306a\u3053\u3068\u306f\u3042\u308a\u307e\u305b\u3093\u3002\u884c\u5217\u306e\u5834\u5408\u3001\u6b21\u5143\u304c1\u3064\u5927\u304d\u304f\u306a\u308b\u3060\u3051\u3067\u884c\u5217\u5f0f\u30fb\u9006\u884c\u5217\u306e\u8a08\u7b97\u306f\u30bf\u30a4\u30d8\u30f3\u306b\u306a\u308a\u307e\u3059\u3002\u30b9\u30e9\u30b9\u30e9\u3068\u624b\u8a08\u7b97\u3067\u304d\u308b\u306e\u306f2\u6b21\u5143\u3069\u307e\u308a\u3067\u3059\u30023\u6b21\u5143\u30014\u6b21\u5143\u306e\u884c\u5217\u306e\u8a08\u7b97\u3067\u3059\u3089\u5bb9\u6613\u306b\u624b\u8a08\u7b97\u3067\u304d\u307e\u305b\u3093\u3002<\/p>\n<p>\u624b\u8a08\u7b97\u304c\u3067\u304d\u306a\u3044\u307e\u307e\u884c\u5217\u5f0f\u30fb\u9006\u884c\u5217\u30fb\u9023\u7acb\u5206\u7a0b\u5f0f\u306e\u4ed5\u7d44\u307f\u3092\u3082\u306e\u306b\u3059\u308b\u3053\u3068\u306f\u3067\u304d\u307e\u305b\u3093\u3002\u8a08\u7b97\u91cf\u306e\u81a8\u5927\u3055\u3053\u305d\u304c\u884c\u5217\u306b\u3068\u3063\u3066\u6700\u5927\u306e\u58c1\u3067\u3059\u3002<\/p>\n<p>\u305d\u3053\u3067Python\u306e\u767b\u5834\u3067\u3059\u3002<\/p>\n<p>\u30d9\u30af\u30c8\u30eb\u3068\u540c\u69d8\u306bNumPy\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u7528\u3044\u3066\u3001\u884c\u5217\u306f\u5bb9\u6613\u306b\u5b9a\u7fa9\u3067\u304d\u3001NumPy\u306b\u7528\u610f\u3055\u308c\u305f\u95a2\u6570\u3092\u7528\u3044\u308b\u3053\u3068\u3067\u884c\u5217\u5f0f\u30fb\u9006\u884c\u5217\u30fb\u9023\u7acb\u5206\u7a0b\u5f0f\u3068\u3044\u3063\u305f\u884c\u5217\u306e\u69d8\u3005\u306a\u8a08\u7b97\u30921\u884c\u306e\u30b3\u30fc\u30c9\u3067\u6e08\u307e\u305b\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n<p>\u3053\u308c\u307e\u3067\u306e\u9023\u8f09\u540c\u69d8\u306bPython\u3067\u7dda\u5f62\u4ee3\u6570\u3092\u5b66\u3076\u3053\u3068\u306f\u3082\u3061\u308d\u3093\u53ef\u80fd\u3067\u3059\u3002\u3057\u304b\u3057\u3001\u305d\u308c\u3067\u3082\u7dda\u5f62\u4ee3\u6570\u306e\u30c6\u30ad\u30b9\u30c8\u306e\u7ae0\u7acb\u3066\u306e\u9577\u3055\u306f\u9577\u3044\u307e\u307e\u5909\u308f\u308b\u3053\u3068\u306f\u3042\u308a\u307e\u305b\u3093\u3002\u7dda\u5f62\u4ee3\u6570\u3068\u306f\u3001\u9023\u7acb\u65b9\u7a0b\u5f0f\u306e\u89e3\u6cd5\u3092\u3044\u304b\u306b\u30b7\u30b9\u30c6\u30de\u30c6\u30a3\u30c3\u30af\u306b\u884c\u3046\u304b\u3068\u3044\u3046\u554f\u984c\u304c\u539f\u70b9\u306b\u3042\u308a\u307e\u3059\u3002<\/p>\n<p>\u306f\u305f\u3057\u3066\u884c\u5217\u3068\u3044\u3046\u65b0\u3057\u3044\u6982\u5ff5\u304c\u8a95\u751f\u3057\u3001\u305d\u3053\u306b\u898b\u4e8b\u306a\u7f8e\u3057\u3044\u6cd5\u5247\u304c\u767a\u898b\u3055\u308c\u3066\u3044\u304f\u3053\u3068\u306b\u306a\u3063\u305f\u306e\u3067\u3059\u3002\u884c\u5217\u306e\u7f8e\u3057\u3044\u6cd5\u5247\u306e\u7d50\u6676\u304c\u7dda\u5f62\u4ee3\u6570\u30fb\u7dda\u5f62\u4ee3\u6570\u5b66\u30fb\u7dda\u578b\u4ee3\u6570\u30fb\u7dda\u578b\u4ee3\u6570\u5b66\uff08\u7528\u8a9e\u306e\u7d44\u307f\u5408\u308f\u305b\u306f4\u901a\u308a\uff09\u3067\u3059\u3002<\/p>\n<p>\u300cNumPy\u3067\u884c\u5217\u300d\u3068\u3057\u3066\u884c\u5217\u306e\u8a08\u7b97\u3092\u7d39\u4ecb\u3057\u3066\u3044\u304d\u307e\u3059\u3002\u884c\u5217\u306f\u9762\u767d\u305d\u3046\u3068\u601d\u3063\u3066\u3082\u3089\u3048\u308b\u30d7\u30ed\u30b0\u30e9\u30e0\u3092\u7528\u610f\u3057\u307e\u3057\u305f\u3002\u305d\u308c\u304c\u56de\u5e30\u5206\u6790\u3067\u3059\u3002<\/p>\n<p>\u591a\u6570\u306e\u30c7\u30fc\u30bf\u3092\u3082\u3063\u3068\u3082\u3046\u307e\u304f\u8fd1\u4f3c\u3059\u308b\u76f4\u7dda\uff08\u66f2\u7dda\uff09\u3092\u6c42\u3081\u308b\u3053\u3068\u3067\u3001\u4e88\u6e2c\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\u3092\u53ef\u80fd\u306b\u3059\u308b\u56de\u5e30\u5206\u6790\u306f\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u306e\u57fa\u672c\u3067\u3059\u3002<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Python%E3%81%AB%E3%82%88%E3%82%8B%E5%9B%9E%E5%B8%B0%E5%88%86%E6%9E%90\"><\/span>Python\u306b\u3088\u308b\u56de\u5e30\u5206\u6790<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u3055\u3063\u305d\u304fPython\u306b\u3088\u308b\u56de\u5e30\u5206\u6790\u306e\u30b3\u30fc\u30c9\u3092\u898b\u3066\u3044\u305f\u3060\u304d\u307e\u3057\u3087\u3046\u3002<\/p>\n<p>\u7528\u610f\u3057\u305f\u30c7\u30fc\u30bf\u306f10\u4eba\u5206\u306e\u8eab\u9577\uff08cm\uff09\u3068\u4f53\u91cd\uff08kg\uff09\u3067\u3059\u3002\u307e\u305a\u3053\u308c\u3089\u3092np.array()\u95a2\u6570\u3092\u7528\u3044\u3066\u8aac\u660e\u5909\u6570\u30d9\u30af\u30c8\u30eb\uff08\u914d\u5217\uff09x\u3068\u76ee\u7684\u5909\u6570\uff08\u4f53\u91cd\uff09\u30d9\u30af\u30c8\u30eby\u3092\u5b9a\u7fa9\u3057\u307e\u3059\u3002<\/p>\n<p>\u6b21\u306b\u8aac\u660e\u5909\u6570\uff08\u8eab\u9577\uff09\u304b\u3089\u8aac\u660e\u5909\u6570\u884c\u5217X\u3092\u5b9a\u7fa9\u3057\u307e\u3059\u3002\u306f\u305f\u3057\u3066\u884c\u5217X\u306b\u5bfe\u3057\u3066\u8ee2\u7f6e\u884c\u5217\u3001\u9006\u884c\u5217\u306e\u8a08\u7b97\u3092\u3057\u3066\u6700\u5f8c\u306b\u76ee\u7684\u5909\u6570\uff08\u4f53\u91cd\uff09\u30d9\u30af\u30c8\u30eby\u3092\u304b\u3051\u308b\u3053\u3068\u3067\u56de\u5e30\u5f0f\u306e\u4fc2\u6570\uff08\u56de\u5e30\u4fc2\u6570\uff09\u304c\u5f97\u3089\u308c\u307e\u3059\u3002\u3053\u306e\u56de\u5e30\u4fc2\u6570\u306e\u8a08\u7b97\u30b3\u30fc\u30c9\u306f\u305f\u3063\u305f1\u884c\u3067\u3059\u3002<\/p>\n<p>\u6700\u5f8c\u306b\u8a08\u7b97\u7d50\u679c\u3092\u51fa\u529b\u3057\u307e\u3059\u3002<\/p>\n<h3><span class=\"ez-toc-section\" id=\"%EF%BC%88%E8%BA%AB%E9%95%B7%E3%81%A8%E4%BD%93%E9%87%8D%EF%BC%89%E5%9B%9E%E5%B8%B0%E5%88%86%E6%9E%90%E3%83%97%E3%83%AD%E3%82%B0%E3%83%A9%E3%83%A0%E3%80%80%E3%80%8Cregression1py%E3%80%8D\"><\/span>\uff08\u8eab\u9577\u3068\u4f53\u91cd\uff09\u56de\u5e30\u5206\u6790\u30d7\u30ed\u30b0\u30e9\u30e0\u3000\u300cregression1.py\u300d<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>&gt;&gt;&gt;\u3000import numpy as np<br \/>\n&gt;&gt;&gt;<br \/>\n&gt;&gt;&gt;\u3000 # \u30c7\u30fc\u30bf\u5b9a\u7fa9<br \/>\n&gt;&gt;&gt;\u3000 x = np.array([170, 166, 157, 164, 157, 160, 163, 160, 153, 165]) # \u8aac\u660e\u5909\u6570 \u8eab\u9577<br \/>\n&gt;&gt;&gt;\u3000 y = np.array([57, 53, 47, 52, 47, 53, 48, 48, 43, 57]) # \u76ee\u7684\u5909\u6570 \u4f53\u91cd<br \/>\n&gt;&gt;&gt;<br \/>\n&gt;&gt;&gt;\u3000 # \u8aac\u660e\u5909\u6570\u884c\u5217X\u306e\u5b9a\u7fa9<br \/>\n&gt;&gt;&gt;\u3000 ones = np.ones(len(x))<br \/>\n&gt;&gt;&gt;\u3000 X = np.array([ones, x]).T<br \/>\n&gt;&gt;&gt;<br \/>\n&gt;&gt;&gt;\u3000 # \u56de\u5e30\u4fc2\u6570\u306e\u8a08\u7b97<br \/>\n&gt;&gt;&gt;\u3000 theta = np.linalg.inv(X.T @ X) @ X.T @ y<br \/>\n&gt;&gt;&gt;<br \/>\n&gt;&gt;&gt;\u3000 print(f&#8217;\u8aac\u660e\u5909\u6570\u884c\u5217 X =\\n {X}&#8217;)<br \/>\n&gt;&gt;&gt;\u3000 print(f&#8217;\u56de\u5e30\u4fc2\u6570 \u03b8_0 = {theta[0]}&#8217;)<br \/>\n&gt;&gt;&gt;\u3000 print(f&#8217;\u56de\u5e30\u4fc2\u6570 \u03b8_1 = {theta[1]}&#8217;)<br \/>\n&gt;&gt;&gt;\u3000 print(f&#8217;\u56de\u5e30\u5f0f y = {theta[0]} + {theta[1]} * x&#8217;)<\/p>\n<p>\u3053\u306e\u30d7\u30ed\u30b0\u30e9\u30e0\u30d5\u30a1\u30a4\u30eb\u306f\u6b21\u304b\u3089\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u3067\u304d\u307e\u3059\u3002<br \/>\n<a href=\"https:\/\/drive.google.com\/file\/d\/1U1m17D--NUpoZ7wTijzbXlHCPfLb6Ibv\/view?usp=sharing\" target=\"_blank\" rel=\"noopener\">https:\/\/drive.google.com\/file\/d\/1U1m17D&#8211;NUpoZ7wTijzbXlHCPfLb6Ibv\/view?usp=sharing<\/a><\/p>\n<h3><span class=\"ez-toc-section\" id=\"%E5%AE%9F%E8%A1%8C%E7%B5%90%E6%9E%9C\"><\/span>\u5b9f\u884c\u7d50\u679c<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>\u6b21\u304cregression1.py\u306e\u5b9f\u884c\u7d50\u679c\u3067\u3059\u3002\u6700\u5f8c\u306b\u56de\u5e30\u5f0f\u304cx\u306e1\u6b21\u5f0f\u3068\u3057\u3066\u51fa\u529b\u3055\u308c\u3066\u3044\u307e\u3059\u3002<\/p>\n<p><img decoding=\"async\" class=\"aligncenter wp-image-17743 size-full\" src=\"https:\/\/club.informatix.co.jp\/wp-content\/uploads\/2022\/07\/20220701-2.jpg\" alt=\"\" width=\"549\" height=\"318\" srcset=\"https:\/\/club.informatix.co.jp\/wp-content\/uploads\/2022\/07\/20220701-2.jpg 549w, https:\/\/club.informatix.co.jp\/wp-content\/uploads\/2022\/07\/20220701-2-300x174.jpg 300w\" sizes=\"(max-width: 549px) 100vw, 549px\" \/><\/p>\n<p>\u3053\u308c\u3088\u308a\u8eab\u9577\u304c175cm\u3067\u3042\u308c\u3070\u4f53\u91cd\u306f\u3044\u304f\u3064\u306b\u306a\u308b\u304b\u8a08\u7b97\u3067\u304d\u307e\u3059\u3002\u56de\u5e30\u5f0f\u306ex\u306b175\u3092\u4ee3\u5165\u3057\u3066\u8a08\u7b97\u3057\u3066\u307f\u307e\u3059\u3002\u7d50\u679c\u306f\u7d0461.3kg\u3067\u3059\u3002<\/p>\n<p>&gt;&gt;&gt;\u3000 -78.77006507593245 + 0.8004338394793968 * 175<br \/>\n&gt;&gt;&gt;\u3000 61.30585683296201<\/p>\n<p>\u3053\u306e\u4f8b\u306e\u3088\u3046\u306b\u8aac\u660e\u5909\u6570\u304c1\u3064\u306e\u5834\u5408\u306b\u306f\u56de\u5e30\u5f0f\u306fx\u306e1\u6b21\u5f0f\u3068\u306a\u308b\u306e\u3067\u3001\u30b0\u30e9\u30d5\u306f\u76f4\u7dda\u3067\u3059\u3002\u3053\u308c\u3092\u56de\u5e30\u76f4\u7dda\u3068\u3044\u3044\u307e\u3059\u3002<\/p>\n<p>10\u4eba\u5206\u306e\u30c7\u30fc\u30bf\u306e\u6563\u5e03\u56f3\u3068\u56de\u5e30\u76f4\u7dda\u3092\u63cf\u304f\u30d7\u30ed\u30b0\u30e9\u30e0\u306f\u3001\u56de\u5e30\u5206\u6790\u30d7\u30ed\u30b0\u30e9\u30e0\u300cregression1.py\u300d\u306bmatplotlib\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u7528\u3044\u305f\u30b0\u30e9\u30d5\u63cf\u753b\u90e8\u5206\u3092\u4ed8\u3051\u52a0\u3048\u305f\u306e\u304c\u56de\u5e30\u5206\u6790\u30d7\u30ed\u30b0\u30e9\u30e0\u300cregression2.py\u300d\u3067\u3059\u3002<\/p>\n<h3><span class=\"ez-toc-section\" id=\"%EF%BC%88%E8%BA%AB%E9%95%B7%E3%81%A8%E4%BD%93%E9%87%8D%EF%BC%89%E5%9B%9E%E5%B8%B0%E5%88%86%E6%9E%90%E3%83%97%E3%83%AD%E3%82%B0%E3%83%A9%E3%83%A0%E3%80%8Cregression2py%E3%80%8D\"><\/span>\uff08\u8eab\u9577\u3068\u4f53\u91cd\uff09\u56de\u5e30\u5206\u6790\u30d7\u30ed\u30b0\u30e9\u30e0\u300cregression2.py\u300d<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>&gt;&gt;&gt;\u3000 import numpy as np<br \/>\n&gt;&gt;&gt;\u3000 import matplotlib.pyplot as plt<br \/>\n&gt;&gt;&gt;<br \/>\n&gt;&gt;&gt;<br \/>\n&gt;&gt;&gt;\u3000 # \u30c7\u30fc\u30bf\u5b9a\u7fa9<br \/>\n&gt;&gt;&gt;\u3000 x = np.array([170, 166, 157, 164, 157, 160, 163, 160, 153, 165]) # \u8aac\u660e\u5909\u6570 \u8eab\u9577<br \/>\n&gt;&gt;&gt;\u3000 y = np.array([57, 53, 47, 52, 47, 53, 48, 48, 43, 57]) # \u76ee\u7684\u5909\u6570 \u4f53\u91cd<br \/>\n&gt;&gt;&gt;<br \/>\n&gt;&gt;&gt;<br \/>\n&gt;&gt;&gt;\u3000 # \u8aac\u660e\u5909\u6570\u884c\u5217X\u306e\u5b9a\u7fa9<br \/>\n&gt;&gt;&gt;\u3000 ones = np.ones(len(x))<br \/>\n&gt;&gt;&gt;\u3000 X = np.array([ones, x]).T<br \/>\n&gt;&gt;&gt;<br \/>\n&gt;&gt;&gt;\u3000 # \u56de\u5e30\u4fc2\u6570\u306e\u8a08\u7b97<br \/>\n&gt;&gt;&gt;\u3000 theta = np.linalg.inv(X.T @ X) @ X.T @ y<br \/>\n&gt;&gt;&gt;<br \/>\n&gt;&gt;&gt;\u3000 print(f&#8217;\u8aac\u660e\u5909\u6570\u884c\u5217 X =\\n {X}&#8217;)<br \/>\n&gt;&gt;&gt;\u3000 print(f&#8217;\u56de\u5e30\u4fc2\u6570 \u03b8_0 = {theta[0]}&#8217;)<br \/>\n&gt;&gt;&gt;\u3000 print(f&#8217;\u56de\u5e30\u4fc2\u6570 \u03b8_1 = {theta[1]}&#8217;)<br \/>\n&gt;&gt;&gt;\u3000 print(f&#8217;\u56de\u5e30\u5f0f y = {theta[0]} + {theta[1]} * x&#8217;)<br \/>\n&gt;&gt;&gt;<br \/>\n&gt;&gt;&gt;\u3000 # \u30c7\u30fc\u30bf\u6563\u5e03\u56f3\u3068\u56de\u5e30\u76f4\u7dda\u3000\u30b0\u30e9\u30d5\u63cf\u753b<br \/>\n&gt;&gt;&gt;\u3000 margin = 1<br \/>\n&gt;&gt;&gt;\u3000 x_min, x_max = x.min()-margin, x.max()+margin # x\u306e\u7bc4\u56f2<br \/>\n&gt;&gt;&gt;\u3000 xx = np.arange(x_min, x_max, 1) # \u56de\u5e30\u76f4\u7dda\u30b0\u30e9\u30d5\u7528\u5909\u6570:xx<br \/>\n&gt;&gt;&gt;<br \/>\n&gt;&gt;&gt;\u3000 # yy = \u03b8_0 + \u03b8_1 * xx # \u56de\u5e30\u76f4\u7dda \u30b0\u30e9\u30d5\u7528\u5909\u6570:xx,yy<br \/>\n&gt;&gt;&gt;\u3000 yy = + theta[0] + theta[1] * xx # \u56de\u5e30\u76f4\u7dda \u30b0\u30e9\u30d5\u7528\u5909\u6570:xx,yy<br \/>\n&gt;&gt;&gt;<br \/>\n&gt;&gt;&gt;\u3000 plt.scatter(x, y, c=&#8217;Blue&#8217;) # \u30c7\u30fc\u30bf\u3092\u9752\u4e38\u3067\u30d7\u30ed\u30c3\u30c8<br \/>\n&gt;&gt;&gt;\u3000 plt.plot(xx, yy, c=&#8217;Red&#8217;) # \u56de\u5e30\u76f4\u7dda\u3092\u8d64\u7dda\u3067\u30d7\u30ed\u30c3\u30c8<br \/>\n&gt;&gt;&gt;\u3000 plt.xlabel(&#8216;x:height(cm)&#8217;)<br \/>\n&gt;&gt;&gt;\u3000 plt.ylabel(&#8216;y:weight(kg)&#8217;)<br \/>\n&gt;&gt;&gt;\u3000 plt.show()<\/p>\n<p>\u3053\u306e\u30d7\u30ed\u30b0\u30e9\u30e0\u30d5\u30a1\u30a4\u30eb\u306f\u6b21\u304b\u3089\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u3067\u304d\u307e\u3059\u3002<br \/>\n<a href=\"https:\/\/drive.google.com\/file\/d\/1ZE5B6X7Sp5ugeBgvb7DZgyEsjsZIE_mg\/view?usp=sharing\" target=\"_blank\" rel=\"noopener\">https:\/\/drive.google.com\/file\/d\/1ZE5B6X7Sp5ugeBgvb7DZgyEsjsZIE_mg\/view?usp=sharing<\/a><\/p>\n<h3><span class=\"ez-toc-section\" id=\"%E5%AE%9F%E8%A1%8C%E7%B5%90%E6%9E%9C-2\"><\/span>\u5b9f\u884c\u7d50\u679c<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><img decoding=\"async\" class=\"aligncenter wp-image-17744 size-full\" src=\"https:\/\/club.informatix.co.jp\/wp-content\/uploads\/2022\/07\/20220701-3.jpg\" alt=\"\" width=\"640\" height=\"442\" srcset=\"https:\/\/club.informatix.co.jp\/wp-content\/uploads\/2022\/07\/20220701-3.jpg 640w, https:\/\/club.informatix.co.jp\/wp-content\/uploads\/2022\/07\/20220701-3-300x207.jpg 300w\" sizes=\"(max-width: 640px) 100vw, 640px\" \/><\/p>\n<h2><span class=\"ez-toc-section\" id=\"numpypolyfit%E9%96%A2%E6%95%B0%E3%82%92%E4%BD%BF%E3%81%A3%E3%81%9F%E5%9B%9E%E5%B8%B0%E5%88%86%E6%9E%90\"><\/span>numpy.polyfit\u95a2\u6570\u3092\u4f7f\u3063\u305f\u56de\u5e30\u5206\u6790<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>NumPy\u30e9\u30a4\u30d6\u30e9\u30ea\u306b\u306f\u56de\u5e30\u5206\u6790\u306e\u305f\u3081\u306epolyfit\u95a2\u6570\u304c\u7528\u610f\u3055\u308c\u3066\u3044\u307e\u3059\u3002\u3053\u308c\u3092\u7528\u3044\u308c\u3070\u30b3\u30fc\u30c9\u306f\u3082\u3063\u3068\u7c21\u5358\u306b\u306a\u308a\u307e\u3059\u3002<br \/>\n&gt;&gt;&gt;\u3000 theta_1 , theta_0 = np.polyfit(x, y, 1)<\/p>\n<p>\u7b2c3\u5f15\u6570\u30921\u3068\u3059\u308b\u3053\u3068\u3067\u56de\u5e30\u5f0f\u30921\u6b21\u5f0f\u3068\u6307\u793a\u3057\u307e\u3059\u3002<br \/>\n\u56de\u5e30\u4fc2\u6570\u306fx\u306e\u4fc2\u6570\uff08theta_1\uff09\u3001\u5207\u7247\uff08theta_0\uff09\u306e\u9806\u5e8f\u3067\u51fa\u529b\u3055\u308c\u307e\u3059\u3002<\/p>\n<h3><span class=\"ez-toc-section\" id=\"%EF%BC%88%E8%BA%AB%E9%95%B7%E3%81%A8%E4%BD%93%E9%87%8D%EF%BC%89%E5%9B%9E%E5%B8%B0%E5%88%86%E6%9E%90%E3%83%97%E3%83%AD%E3%82%B0%E3%83%A9%E3%83%A0%E3%80%8Cregression3py%E3%80%8D\"><\/span>\uff08\u8eab\u9577\u3068\u4f53\u91cd\uff09\u56de\u5e30\u5206\u6790\u30d7\u30ed\u30b0\u30e9\u30e0\u300cregression3.py\u300d<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>&gt;&gt;&gt;\u3000 import matplotlib.pyplot as plt<br \/>\n&gt;&gt;&gt;<br \/>\n&gt;&gt;&gt;\u3000 # \u30c7\u30fc\u30bf\u5b9a\u7fa9<br \/>\n&gt;&gt;&gt;\u3000 x = np.array([170, 166, 157, 164, 157, 160, 163, 160, 153, 165]) # \u8aac\u660e\u5909\u6570 \u8eab\u9577<br \/>\n&gt;&gt;&gt;\u3000 y = np.array([57, 53, 47, 52, 47, 53, 48, 48, 43, 57]) # \u76ee\u7684\u5909\u6570 \u4f53\u91cd<br \/>\n&gt;&gt;&gt;<br \/>\n&gt;&gt;&gt;\u3000 # \u56de\u5e30\u4fc2\u6570\u306e\u8a08\u7b97<br \/>\n&gt;&gt;&gt;\u3000 theta_1 , theta_0 = np.polyfit(x, y, 1)<br \/>\n&gt;&gt;&gt;<br \/>\n&gt;&gt;&gt;\u3000 print(f&#8217;\u56de\u5e30\u4fc2\u6570 \u03b8_0 = {theta_0}&#8217;)<br \/>\n&gt;&gt;&gt;\u3000 print(f&#8217;\u56de\u5e30\u4fc2\u6570 \u03b8_1 = {theta_1}&#8217;)<br \/>\n&gt;&gt;&gt;\u3000 print(f&#8217;\u56de\u5e30\u5f0f y = {theta_0} + {theta_1} * x&#8217;)<br \/>\n&gt;&gt;&gt;<br \/>\n&gt;&gt;&gt;\u3000 # \u30c7\u30fc\u30bf\u6563\u5e03\u56f3\u3068\u56de\u5e30\u76f4\u7dda\u3000\u30b0\u30e9\u30d5\u63cf\u753b<br \/>\n&gt;&gt;&gt;\u3000 margin = 1<br \/>\n&gt;&gt;&gt;\u3000 x_min, x_max = x.min()-margin, x.max()+margin # x\u306e\u7bc4\u56f2<br \/>\n&gt;&gt;&gt;\u3000 xx = np.arange(x_min, x_max, 1) # \u56de\u5e30\u76f4\u7dda\u30b0\u30e9\u30d5\u7528\u5909\u6570:xx<br \/>\n&gt;&gt;&gt;<br \/>\n&gt;&gt;&gt;\u3000 # yy = \u03b8_0 + \u03b8_1 * xx # \u56de\u5e30\u76f4\u7dda \u30b0\u30e9\u30d5\u7528\u5909\u6570:xx,yy<br \/>\n&gt;&gt;&gt;\u3000 yy = + theta_0 + theta_1 * xx # \u56de\u5e30\u76f4\u7dda \u30b0\u30e9\u30d5\u7528\u5909\u6570:xx,yy<br \/>\n&gt;&gt;&gt;<br \/>\n&gt;&gt;&gt;\u3000 plt.scatter(x, y, c=&#8217;Blue&#8217;) # \u30c7\u30fc\u30bf\u3092\u9752\u4e38\u3067\u30d7\u30ed\u30c3\u30c8<br \/>\n&gt;&gt;&gt;\u3000 plt.plot(xx, yy, c=&#8217;Red&#8217;) # \u56de\u5e30\u76f4\u7dda\u3092\u8d64\u7dda\u3067\u30d7\u30ed\u30c3\u30c8<br \/>\n&gt;&gt;&gt;\u3000 plt.xlabel(&#8216;x:height(cm)&#8217;)<br \/>\n&gt;&gt;&gt;\u3000 plt.ylabel(&#8216;y:weight(kg)&#8217;)<br \/>\n&gt;&gt;&gt;\u3000 plt.show()<\/p>\n<p>\u3053\u306e\u30d7\u30ed\u30b0\u30e9\u30e0\u30d5\u30a1\u30a4\u30eb\u306f\u6b21\u304b\u3089\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u3067\u304d\u307e\u3059\u3002<br \/>\n<a href=\"https:\/\/drive.google.com\/file\/d\/1X5KCOubqdvUyl5NPIBMthXbqdfTFfjwj\/view?usp=sharing\" target=\"_blank\" rel=\"noopener\">https:\/\/drive.google.com\/file\/d\/1X5KCOubqdvUyl5NPIBMthXbqdfTFfjwj\/view?usp=sharing<\/a><\/p>\n<h3><span class=\"ez-toc-section\" id=\"%E5%AE%9F%E8%A1%8C%E7%B5%90%E6%9E%9C-3\"><\/span>\u5b9f\u884c\u7d50\u679c<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><img decoding=\"async\" class=\"aligncenter wp-image-17740 size-full\" src=\"https:\/\/club.informatix.co.jp\/wp-content\/uploads\/2022\/07\/20220701-4.jpg\" alt=\"\" width=\"545\" height=\"92\" srcset=\"https:\/\/club.informatix.co.jp\/wp-content\/uploads\/2022\/07\/20220701-4.jpg 545w, https:\/\/club.informatix.co.jp\/wp-content\/uploads\/2022\/07\/20220701-4-300x51.jpg 300w\" sizes=\"(max-width: 545px) 100vw, 545px\" \/><\/p>\n<p><img decoding=\"async\" class=\"aligncenter wp-image-17741 size-full\" src=\"https:\/\/club.informatix.co.jp\/wp-content\/uploads\/2022\/07\/20220701-5.jpg\" alt=\"\" width=\"640\" height=\"441\" srcset=\"https:\/\/club.informatix.co.jp\/wp-content\/uploads\/2022\/07\/20220701-5.jpg 640w, https:\/\/club.informatix.co.jp\/wp-content\/uploads\/2022\/07\/20220701-5-300x207.jpg 300w\" sizes=\"(max-width: 640px) 100vw, 640px\" \/><\/p>\n<p>\u56de\u5e30\u4fc2\u6570\u306f\u5148\u306e\u7d50\u679c\u3068\u307b\u307c\u540c\u3058\u7d50\u679c\u306b\u306a\u308b\u3053\u3068\u304c\u78ba\u8a8d\u3067\u304d\u307e\u3059\u3002<\/p>\n<h3><span class=\"ez-toc-section\" id=\"%E5%9B%9E%E5%B8%B0%E5%88%86%E6%9E%90%E3%81%AE%E9%8D%B5%E3%80%8C%E6%9C%80%E5%B0%8F2%E4%B9%97%E6%B3%95%E3%80%8D\"><\/span>\u56de\u5e30\u5206\u6790\u306e\u9375\u300c\u6700\u5c0f2\u4e57\u6cd5\u300d<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>\u3044\u304b\u304c\u3067\u3057\u305f\u3067\u3057\u3087\u3046\u304b\u3002\u8eab\u9577\u3001\u4f53\u91cd\u306e\u30c7\u30fc\u30bf\u3092\u8fd1\u4f3c\u3059\u308b\u56de\u5e30\u76f4\u7dda\u3092\u6c42\u3081\u308b\u30b3\u30fc\u30c9\u306f\u3053\u306e\u3088\u3046\u306b\u6570\u884c\u3067\u3067\u304d\u3066\u3057\u307e\u3044\u307e\u3059\u3002\u305d\u308c\u3082\u3053\u308c\u3082\u6b21\u306e1\u884c\u306e\u304a\u304b\u3052\u3067\u3059\u3002<\/p>\n<p>&gt;&gt;&gt;\u3000 # \u56de\u5e30\u4fc2\u6570\u306e\u8a08\u7b97<br \/>\n&gt;&gt;&gt;\u3000 theta = np.linalg.inv(X.T @ X) @ X.T @ y<\/p>\n<p>\u306a\u305c\u3053\u306e\u3088\u3046\u306a\u884c\u5217\u306e\u8a08\u7b97\uff08\u884c\u5217\u306e\u7a4d\u3001\u8ee2\u7f6e\u884c\u5217\u3001\u9006\u884c\u5217\uff09\u306b\u3088\u3063\u3066\u56de\u5e30\u4fc2\u6570\u304c\u5f97\u3089\u308c\u308b\u306e\u304b\u3002\u4eca\u5f8c\u306e\u9023\u8f09\u3067\u3058\u3063\u304f\u308a\u898b\u3066\u3044\u304d\u305f\u3044\u3068\u601d\u3044\u307e\u3059\u3002\u305d\u3053\u3067\u5c55\u958b\u3055\u308c\u308b\u306e\u306f\u9a5a\u304d\u306e\u9023\u7d9a\u3067\u3059\u3002<\/p>\n<p>\u6642\u4ee3\u306f\u4eca\u304b\u3089200\u5e74\u524d\u306e\u30d5\u30e9\u30f3\u30b9\u306b\u9061\u308a\u307e\u3059\u30021789\u5e747\u670814\u65e5\u3001\u30d0\u30b9\u30c6\u30a3\u30fc\u30e6\u8972\u6483\u304c\u8d77\u304d\u307e\u3059\u3002\u6240\u8b02\u3001\u30d5\u30e9\u30f3\u30b9\u9769\u547d\u3067\u3059\u3002\u30d5\u30e9\u30f3\u30b9\u9769\u547d\u306e\u4e2d\u3067\u751f\u307e\u308c\u305f\u306e\u304c\u30e1\u30fc\u30c8\u30eb\u3067\u3059\u3002<\/p>\n<p>\u767b\u5834\u4eba\u7269\u306f\u5168\u54e1\u6570\u5b66\u8005\u3001\u30e9\u30b0\u30e9\u30f3\u30b8\u30e5\u3001\u30e9\u30d7\u30e9\u30b9\u3001\u30c9\u30e9\u30f3\u30d6\u30eb\u305d\u3057\u3066\u30ac\u30a6\u30b9\u3002\u30e1\u30fc\u30c8\u30eb\u3068\u3044\u3046\u7d71\u4e00\u5358\u4f4d\u3092\u3064\u304f\u308b\u305f\u3081\u306b\u6570\u5b66\u306f\u7dcf\u52d5\u54e1\u3055\u308c\u307e\u3057\u305f\u3002\u306f\u305f\u3057\u3066\u5f7c\u3089\u306e\u95d8\u3044\u306e\u4e2d\u304b\u3089\u65b0\u3057\u3044\u6570\u5b66\u2500\u2500\u6700\u5c0f2\u4e57\u6cd5\u304c\u8a95\u751f\u3057\u307e\u3057\u305f\u3002\u6700\u5c0f2\u4e57\u6cd5\u306e\u304a\u304b\u3052\u3067\u56de\u5e30\u4fc2\u6570\u306e\u8a08\u7b97\u304c\u53ef\u80fd\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n<p>\u4e0a\u8a18\u306e1\u884c\u306e\u6570\u5f0f\u306f\u3001\u884c\u5217\u3068\u30e1\u30fc\u30c8\u30eb\u3068\u30d5\u30e9\u30f3\u30b9\u9769\u547d\u3068\u3044\u3046\u58ee\u5927\u306a\u7269\u8a9e\u304b\u3089\u751f\u307f\u3060\u3055\u308c\u307e\u3057\u305f\u3002\u6b21\u56de\u4ee5\u964d\u3092\u3054\u671f\u5f85\u304f\u3060\u3055\u3044\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u7dda\u5f62\u4ee3\u6570\u306f\u30bf\u30a4\u30d8\u30f3 \u524d\u56de\u30fb\u524d\u3005\u56de\u3001\u30d9\u30af\u30c8\u30eb\u3092\u53d6\u308a\u4e0a\u3052\u307e\u3057\u305f\u3002\u30d9\u30af\u30c8\u30eb\u306e\u6b21\u3068\u3044\u3046\u3053\u3068\u3067\u884c\u5217\u3092\u306f\u3058\u3081\u3066\u3044\u304d\u307e\u3059\u3002\u30d9\u30af\u30c8\u30eb\u3068\u884c\u5217\u306f\u7dda\u5f62\u4ee3\u6570\u5b66\u3068\u3044\u3046\u5927\u304d\u306a\u6570\u5b66\u3078\u3068\u7d50\u5b9f\u3057\u307e\u3059\u3002 1\u518a\u306b\u307e\u3068\u3081\u3089\u308c\u305f\u7dda\u5f62\u4ee3\u6570\u306e\u30c6\u30ad &#8230; 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